Abstract
This work presents research in the field of machine translation for the Kazakh language. A comparative analysis of translation works of open online machine translation systems (Google translate, Yandex translate, sozdik.kz, webtran.ru.) for English-Kazakh and Russian-Kazakh translation is presented. To improve the quality of translation for the Kazakh language a model of post-editing of the Kazakh language in machine translation has been developed, based on the neural network training approach. For machine learning parallel corpuses for the English-Kazakh and Russian-Kazakh language pairs were collected and processed. Experimental testing has been carried out. The results obtained were evaluated using the BLEU metric.
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Acknowledgments
This research was performed and financed by the grant Project IRN AP08052421 Ministry of education and science of the Republic of Kazakhstan.
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Rakhimova, D., Sagat, K., Zhakypbaeva, K., Zhunussova, A. (2021). Development and Study of a Post-editing Model for Russian-Kazakh and English-Kazakh Translation Based on Machine Learning. In: Wojtkiewicz, K., Treur, J., Pimenidis, E., Maleszka, M. (eds) Advances in Computational Collective Intelligence. ICCCI 2021. Communications in Computer and Information Science, vol 1463. Springer, Cham. https://doi.org/10.1007/978-3-030-88113-9_42
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